a. Field of the Invention
This invention relates to an automated on-line hand written data verification system, for example for high accuracy signature identification, based on scriber movement and data analysis using digital data comparison. More particularly, it relates to an identification system using hand written data, and which takes into account evaluation of the maximum value of cross-correlation function between to-be-verified and reference signature signals, as well as analysis of phase histograms relate to such signals.
b. Discussion of the Prior Art
The dictionary defines a signature as the name of a person written with his own hand. It is the one of oldest means used by people to signify authenticity, and still remains the primary means of authorization approval and authentication. The current electronic environment of computer networks, facsimile machines, and on-line data bases, coupled with movement towards a money-less, paper-less, faceless society requires new and innovative ways to guarantee the authencity and validity of money and document transactions. One way to protect information is encryption which provides a certain amount of security. Modern encryption systems use a pair of encryption keys, a public encryption key and a private secret decryption key. However, should the private decryption key of an individual be learned by an unauthorized person, the system loses its security.
In the art, two basic machine method approaches to signature authentication process are known, the "method of templets" and the "correlation analysis method."
The method of templets uses a set of chosen feature values represented together with their tolerance levels and with corresponding weight coefficients. The features that represent the signature of a person usually exploit such characteristics as the average number of peaks, the position of the highest peak, the number of cross-overs at the zero reference, and the like, that is an image of the average signature dynamics as it used in the pattern recognition approach. Since the signature of a person is highly variable, it is very hard to find its invariant. This fact results in a reliability problem when using the method of templets for signature verification.
The correlation analysis method is more appropriate to the nature of the problem of comparison of signature dynamic signals. However, the correlation analysis method runs into difficulties because of the short length of the signals and the nonstationary character of the signals. Application of the correlation analysis method of signature verification is the subject of Herbst, et al. U.S. Pat. Nos. 3,983,535 and 4,128,829; and Gundersen U.S. Pat. No. 4,736,445. Each of these patents use a regional correlation analysis approach in order to eliminate "distortions of signals in the time axis", for example, see Gundersen U.S. Pat. No. 4,736,445, at Col. 1, lines 52-54. The method of the signal segmentation for cross-correlation analysis was first introduced by Herbst, et al U.S. Pat. No. 3,983,535, and was modified and supplemented by elements of spectrum analysis by Gundersen U.S. Pat. No. 4,736,445. In the reference, the evaluation of cross-correlation functions are done between small segments of corresponding to-be-verified and reference signature signals.
The segmentation in its last modification as taught by Gundersen is implemented by dividing the time signal segments between scriber lifts into short signature segments, each segment being at most 0.7 second in length, with the cross-correlation function being evaluted between corresponding pairs of sub-segments of a to-be-verified signature and of a reference signature. Similarity of the signals is measured by integral characteristics evaluated by using maximum correlation coefficients for all the sub-segment pairs, with special weight functions being used for penalizing any abnormal correlations within the very small overlapped area based on the information about the position of maximum correlation function. Such a segmentation analysis method has serious shortcomings. Splitting segments into sub-segments of very short length results in the considerable loss of useful authentic information. Computation of correlation functions on such short overlapping pieces of these sub-segments can not result in reliable evaluation and makes this measure statistically unstable. Furthermore, the subdivision of segments into very short sub-segments does not eliminate time distortions as it does not result in generation of phase-coincidental pairs of sub-segments from the reference signature and from the to-be-verified signature signals.